Optimal discrete model reduction by multipoint Padé approximation

T. Nigel Lucas

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

A discrete-time multipoint Padé approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Padé approximants. An important result that relates the optimal model to multipoint Padé approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.
Original languageEnglish
Pages (from-to)855-867
Number of pages13
JournalJournal of the Franklin Institute
Volume330
Issue number5
DOIs
Publication statusPublished - Sep 1993

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Model Reduction
Discrete Model
Reduced Order Model
Approximation
Linear equations
Approximation Methods
Linear equation
Discrete-time
Numerical Examples
Model

Cite this

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abstract = "A discrete-time multipoint Pad{\'e} approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Pad{\'e} approximants. An important result that relates the optimal model to multipoint Pad{\'e} approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.",
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Optimal discrete model reduction by multipoint Padé approximation. / Lucas, T. Nigel.

In: Journal of the Franklin Institute, Vol. 330, No. 5, 09.1993, p. 855-867.

Research output: Contribution to journalArticle

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AB - A discrete-time multipoint Padé approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Padé approximants. An important result that relates the optimal model to multipoint Padé approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.

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